Q22-23

Questions 22, 23, 25

## Create survey object.
options(digits = 4)
options(survey.lonely.psu = "adjust")
des <- svydesign(ids = ~1, weights = ~weight, data = df[is.na(df$weight)==F, ])

Q22. Do you do any of the following when you have influenza symptoms?

# subset question data, rename columns, gather into single column
q22_df <- df %>%
  select(CaseID, PPGENDER, PPAGE, ppagecat, PPETHM, PPINCIMP, PPEDUC, PPEDUCAT,
         work, PPWORK, marital, PPMARIT, PPMSACAT, ppreg9, PPSTATEN, PPHOUSE, PPRENT, PPNET, Q22_1:Q22_9, weight) %>%
  rename("Q22_1_Go.to.a.doctor_s.office.or.medical.clinic" = Q22_1,
         "Q22_2_Decide.on.treatment.without.consulting.a.health.practitioner" = Q22_2,
         "Q22_3_Search.the.internet.for.a.treatment" = Q22_3,
         "Q22_4_Get.adequate.sleep" = Q22_4,
         "Q22_5_Eat.nutritious.food" = Q22_5,
         "Q22_6_Take-over-counter.medication.for.symptoms" = Q22_6,
         "Q22_7_Take.an.antiviral.medicine" = Q22_7,
         "Q22_8_Take.no.action.to.treat.the.illness" = Q22_8,
         "Q22_9_Other" = Q22_9) %>%
  gather(Q22_q, Q22_r, Q22_1_Go.to.a.doctor_s.office.or.medical.clinic:Q22_8_Take.no.action.to.treat.the.illness,
         na.rm = T) %>%
  mutate(Q22_q = as.factor(Q22_q))%>%
  mutate(Q22_r = factor(Q22_r, levels = c("Always", "Sometimes", "Never")))
# survey design
options(digits = 4)
options(survey.lonely.psu = "adjust")
des22 <- svydesign(ids = ~1, weights = ~weight, data = q22_df[is.na(q22_df$weight)==F, ])

# weighted data frame
q22 <- data.frame(svytable(~Q22_q + Q22_r + PPGENDER + ppagecat + PPETHM + PPINCIMP, des22, round = T))
# plot templates
title <- ggtitle("Do you do any of the following when you have influenza symptoms?")
## main plot
p <- ggplot(q22, aes(Q22_q, weight = Freq)) + ptext
p + geom_bar(position = 'fill') + aes(fill = Q22_r) + title + coord_flip()

p2 <- ggplot(q22, aes(Q22_q, weight = Freq)) + ptext
p2 + geom_bar(position = "fill") + aes(Q22_q, fill = Q22_r) + coord_flip()

p2 + geom_bar() + aes(Q22_r, fill = Q22_r) + facet_wrap(~Q22_q) + ptext2

p2 + geom_bar() + aes(Q22_q, fill = Q22_q) + facet_wrap(~Q22_r) + ptext2

# by gender
p2 + geom_bar() + aes(PPGENDER, fill = Q22_r) + facet_wrap(~Q22_q) + ggtitle("By gender")

p2 + geom_bar(position = "fill") + aes(PPGENDER, fill = Q22_r) + facet_wrap(~Q22_q)

p2 + geom_bar() + aes(Q22_q, fill = PPGENDER) + facet_wrap(~Q22_r)

p2 + geom_bar(position = 'fill') + aes(Q22_q, fill = PPGENDER) + facet_wrap(~Q22_r) + ggtitle("By gender")

p2 + geom_bar() + aes(PPGENDER, fill = PPGENDER) + facet_grid(Q22_q~Q22_r) + coord_flip() + ptext2

# by age group
p2 + geom_bar() + aes(ppagecat, fill = Q22_r) + facet_wrap(~Q22_q) + ggtitle("By age group")

p2 + geom_bar(position = "fill") + aes(ppagecat, fill = Q22_r) + facet_wrap(~Q22_q)

p2 + geom_bar() + aes(Q22_q, fill = ppagecat) + facet_wrap(~Q22_r)

p2 + geom_bar(position = 'fill') + aes(Q22_q, fill = ppagecat) + facet_wrap(~Q22_r) + ggtitle("By age group")

p2 + geom_bar() + aes(ppagecat, fill = ppagecat) + facet_grid(Q22_q~Q22_r) + ptext2

# by ethnic group
p2 + geom_bar() + aes(PPETHM, fill = Q22_r) + facet_wrap(~Q22_q) + ggtitle("By ethnic group")

p2 + geom_bar(position = "fill") + aes(PPETHM, fill = Q22_r) + facet_wrap(~Q22_q)

p2 + geom_bar() + aes(Q22_q, fill = PPETHM) + facet_wrap(~Q22_r)

p2 + geom_bar(position = 'fill') + aes(Q22_q, fill = PPETHM) + facet_wrap(~Q22_r) + ggtitle("By ethnic group")

p2 + geom_bar() + aes(PPETHM, fill = PPETHM) + facet_grid(Q22_q~Q22_r) + ptext2

p2 + geom_bar() + aes(Q22_r, fill = Q22_r) + facet_grid(Q22_q~PPETHM) + ptext2

# by income
p2 + geom_bar() + aes(PPINCIMP, fill = Q22_r) + facet_wrap(~Q22_q) + ggtitle("By income") + ptext2

p2 + geom_bar(position = "fill") + aes(PPINCIMP, fill = Q22_r) + facet_wrap(~Q22_q) + ptext2

p2 + geom_bar() + aes(Q22_q, fill = PPINCIMP) + facet_wrap(~Q22_r)

p2 + geom_bar(position = 'fill') + aes(Q22_q, fill = PPINCIMP) + facet_wrap(~Q22_r) + ggtitle("By income group")

p2 + geom_bar() + aes(PPINCIMP, fill = PPINCIMP) + facet_grid(Q22_q~Q22_r) + ptext2

Education, work, marital status

# update weighted data frame
q22.2 <- data.frame(svytable(~Q22_q + Q22_r + PPEDUC + PPEDUCAT + work + PPWORK + marital + PPMARIT, des22, round = T))
# restate plots
p3 <- ggplot(q22.2, aes(Q22_q, weight = Freq)) + ptext

# by education
p3 + geom_bar() + aes(PPEDUCAT, fill = Q22_r) + facet_wrap(~Q22_q) + ggtitle("By education")

p3 + geom_bar(position = "fill") + aes(PPEDUCAT, fill = Q22_r) + facet_wrap(~Q22_q)

p3 + geom_bar() + aes(Q22_q, fill = PPEDUCAT) + facet_wrap(~Q22_r)

p3 + geom_bar(position = "fill") + aes(Q22_q, fill = PPEDUCAT) + facet_wrap(~Q22_r) + ggtitle("By education")

p3 + geom_bar() + aes(PPEDUCAT, fill = PPEDUCAT) + facet_grid(Q22_q~Q22_r) + ptext2

p3 + geom_bar() + aes(Q22_r, fill = Q22_r) + facet_grid(Q22_q~PPEDUCAT) + ptext2

# by work
p3 + geom_bar() + aes(work, fill = Q22_r) + facet_wrap(~Q22_q) + ggtitle("By employment status")

p3 + geom_bar(position = "fill") + aes(work, fill = Q22_r) + facet_wrap(~Q22_q)

# by marital
p3 + geom_bar() + aes(marital, fill = Q22_r) + facet_wrap(~Q22_q) + ggtitle("By marital status")

p3 + geom_bar(position = "fill") + aes(marital, fill = Q22_r) + facet_wrap(~Q22_q)

Metro status, region, state, house type, housing status, internet availability

# update weighted data frame
q22.3 <- data.frame(svytable(~Q22_q + Q22_r + PPMSACAT + ppreg9 + PPSTATEN + PPHOUSE + PPRENT + PPNET, des22, round = T))
# restate plots
p4 <- ggplot(q22.3, aes(Q22_q, weight = Freq)) + ptext

# by metro status
p4 + geom_bar(position = "fill") + aes(Q22_r, fill = PPMSACAT) + facet_wrap(~Q22_q) + ggtitle("By metro status")

p4 + geom_bar(position = "fill") + aes(PPMSACAT, fill = Q22_r) + facet_wrap(~Q22_q)

# by region
p4 + geom_bar(position = "fill") + aes(Q22_r, fill = ppreg9) + facet_wrap(~Q22_q) + ggtitle("By region")

p4 + geom_bar() + aes(ppreg9, fill = Q22_r) + facet_wrap(~Q22_q) + ggtitle("By region")

# by state
p4 + geom_bar() + aes(Q22_r, fill = PPSTATEN) + facet_wrap(~Q22_q) + ggtitle("By state")

p4 + geom_bar() + aes(PPSTATEN, fill = Q22_q) + coord_flip() + ggtitle("By state")

# by house type
p4 + geom_bar(position = "fill") + aes(Q22_r, fill = PPHOUSE) + facet_wrap(~Q22_q)

p4 + geom_bar(position = "fill") + aes(fill = PPHOUSE) + ggtitle("By house type")

# housing status
p4 + geom_bar(position = "fill") + aes(Q22_r, fill = PPHOUSE) + facet_wrap(~Q22_q)

p4 + geom_bar() + aes(PPHOUSE, fill = Q22_r) + facet_wrap(~Q22_q) + ggtitle("By housing")

# by internet availability
p4 + geom_bar(position = "fill") + aes(Q22_r, fill = PPNET) + facet_wrap(~Q22_q)

p4 + geom_bar(position = "fill") + aes(PPNET, fill = Q22_r) + facet_wrap(~Q22_q) + ggtitle("By internet availability")

Q23. Which of the following actions do you take when you have influenza symptoms to avoid someone else from getting sick?

# subset question data, rename columns, gather into single column
q23_df <- df %>%
  select(CaseID, PPGENDER, PPAGE, ppagecat, PPETHM, PPINCIMP, PPEDUC, PPEDUCAT,
         work, PPWORK, marital, PPMARIT, PPMSACAT, ppreg9, PPSTATEN, PPHOUSE, PPRENT, PPNET, Q23_1:Q23_11, weight) %>%
  gather(Q23_q, Q23_r, Q23_1:Q23_11, na.rm = T) %>%
  mutate(Q23_q = as.factor(Q23_q))
# survey design
options(digits = 4)
options(survey.lonely.psu = "adjust")
des23 <- svydesign(ids = ~1, weights = ~weight, data = q23_df[is.na(q23_df$weight)==F, ])

Gender, age, ethnicity, income

# weighted data frame
q23 <- data.frame(svytable(~Q23_q + Q23_r + PPGENDER + ppagecat + PPETHM + PPINCIMP, des23, round = T))
# plot templates
title <- ggtitle("Which of the following actions do you take when you have influenza symptoms to avoid someone else from getting sick?")
## main plot
p <- ggplot(q23, aes(Q23_q, weight = Freq)) + ptext
p + geom_bar(position = 'fill') + aes(fill = Q23_r) + title

p2 <- ggplot(q23, aes(Q23_q, weight = Freq)) + ptext
p2 + geom_bar(position = "fill") + aes(Q23_q, fill = Q23_r)

p2 + geom_bar() + aes(Q23_r, fill = Q23_r) + facet_wrap(~Q23_q) + ptext2

p2 + geom_bar() + aes(Q23_q, fill = Q23_q) + facet_wrap(~Q23_r) + ptext2

# by gender
p2 + geom_bar() + aes(PPGENDER, fill = Q23_r) + facet_wrap(~Q23_q) + ggtitle("By gender")

p2 + geom_bar(position = "fill") + aes(PPGENDER, fill = Q23_r) + facet_wrap(~Q23_q)

p2 + geom_bar() + aes(Q23_q, fill = PPGENDER) + facet_wrap(~Q23_r)

p2 + geom_bar(position = 'fill') + aes(Q23_q, fill = PPGENDER) + facet_wrap(~Q23_r) + ggtitle("By gender")

p2 + geom_bar() + aes(PPGENDER, fill = PPGENDER) + facet_grid(Q23_q~Q23_r) + coord_flip() + ptext2

# by age group
p2 + geom_bar() + aes(ppagecat, fill = Q23_r) + facet_wrap(~Q23_q) + ggtitle("By age group")

p2 + geom_bar(position = "fill") + aes(ppagecat, fill = Q23_r) + facet_wrap(~Q23_q)

p2 + geom_bar() + aes(Q23_q, fill = ppagecat) + facet_wrap(~Q23_r)

p2 + geom_bar(position = 'fill') + aes(Q23_q, fill = ppagecat) + facet_wrap(~Q23_r) + ggtitle("By age group")

p2 + geom_bar() + aes(ppagecat, fill = ppagecat) + facet_grid(Q23_q~Q23_r) + ptext2

# by ethnic group
p2 + geom_bar() + aes(PPETHM, fill = Q23_r) + facet_wrap(~Q23_q) + ggtitle("By ethnic group")

p2 + geom_bar(position = "fill") + aes(PPETHM, fill = Q23_r) + facet_wrap(~Q23_q)

p2 + geom_bar() + aes(Q23_q, fill = PPETHM) + facet_wrap(~Q23_r)

p2 + geom_bar(position = 'fill') + aes(Q23_q, fill = PPETHM) + facet_wrap(~Q23_r) + ggtitle("By ethnic group")

p2 + geom_bar() + aes(PPETHM, fill = PPETHM) + facet_grid(Q23_q~Q23_r) + ptext2

p2 + geom_bar() + aes(Q23_r, fill = Q23_r) + facet_grid(Q23_q~PPETHM) + ptext2

# by income
p2 + geom_bar() + aes(PPINCIMP, fill = Q23_r) + facet_wrap(~Q23_q) + ggtitle("By income") + ptext2

p2 + geom_bar(position = "fill") + aes(PPINCIMP, fill = Q23_r) + facet_wrap(~Q23_q) + ptext2

p2 + geom_bar() + aes(Q23_q, fill = PPINCIMP) + facet_wrap(~Q23_r)

p2 + geom_bar(position = 'fill') + aes(Q23_q, fill = PPINCIMP) + facet_wrap(~Q23_r) + ggtitle("By income group")

p2 + geom_bar() + aes(PPINCIMP, fill = PPINCIMP) + facet_grid(Q23_q~Q23_r) + ptext2

Education, work, marital status

# update weighted data frame
q23.2 <- data.frame(svytable(~Q23_q + Q23_r + PPEDUC + PPEDUCAT + work + PPWORK + marital + PPMARIT, des23, round = T))
# restate plots
p3 <- ggplot(q23.2, aes(Q23_q, weight = Freq)) + ptext

# by education
p3 + geom_bar() + aes(PPEDUCAT, fill = Q23_r) + facet_wrap(~Q23_q) + ggtitle("By education")

p3 + geom_bar(position = "fill") + aes(PPEDUCAT, fill = Q23_r) + facet_wrap(~Q23_q)

p3 + geom_bar() + aes(Q23_q, fill = PPEDUCAT) + facet_wrap(~Q23_r)

p3 + geom_bar(position = "fill") + aes(Q23_q, fill = PPEDUCAT) + facet_wrap(~Q23_r) + ggtitle("By education")

p3 + geom_bar() + aes(PPEDUCAT, fill = PPEDUCAT) + facet_grid(Q23_q~Q23_r) + ptext2

p3 + geom_bar() + aes(Q23_r, fill = Q23_r) + facet_grid(Q23_q~PPEDUCAT) + ptext2

# by work
p3 + geom_bar() + aes(work, fill = Q23_r) + facet_wrap(~Q23_q) + ggtitle("By employment status")

p3 + geom_bar(position = "fill") + aes(work, fill = Q23_r) + facet_wrap(~Q23_q)

# by marital
p3 + geom_bar() + aes(marital, fill = Q23_r) + facet_wrap(~Q23_q) + ggtitle("By marital status")

p3 + geom_bar(position = "fill") + aes(marital, fill = Q23_r) + facet_wrap(~Q23_q)

Metro status, region, state, house type, housing status, internet availability

# update weighted data frame
q23.3 <- data.frame(svytable(~Q23_q + Q23_r + PPMSACAT + ppreg9 + PPSTATEN + PPHOUSE + PPRENT + PPNET, des23, round = T))
# restate plots
p4 <- ggplot(q23.3, aes(Q23_q, weight = Freq)) + ptext

# by metro status
p4 + geom_bar(position = "fill") + aes(Q23_r, fill = PPMSACAT) + facet_wrap(~Q23_q) + ggtitle("By metro status")

p4 + geom_bar(position = "fill") + aes(PPMSACAT, fill = Q23_r) + facet_wrap(~Q23_q)

# by region
p4 + geom_bar(position = "fill") + aes(Q23_r, fill = ppreg9) + facet_wrap(~Q23_q) + ggtitle("By region")

p4 + geom_bar() + aes(ppreg9, fill = Q23_r) + facet_wrap(~Q23_q) + ggtitle("By region")

# by state
p4 + geom_bar() + aes(Q23_r, fill = PPSTATEN) + facet_wrap(~Q23_q) + ggtitle("By state")

p4 + geom_bar() + aes(PPSTATEN, fill = Q23_q) + coord_flip() + ggtitle("By state")

# by house type
p4 + geom_bar(position = "fill") + aes(Q23_r, fill = PPHOUSE) + facet_wrap(~Q23_q)

p4 + geom_bar(position = "fill") + aes(fill = PPHOUSE) + ggtitle("By house type")

# housing status
p4 + geom_bar(position = "fill") + aes(Q23_r, fill = PPHOUSE) + facet_wrap(~Q23_q)

p4 + geom_bar() + aes(PPHOUSE, fill = Q23_r) + facet_wrap(~Q23_q) + ggtitle("By housing")

# by internet availability
p4 + geom_bar(position = "fill") + aes(Q23_r, fill = PPNET) + facet_wrap(~Q23_q)

p4 + geom_bar(position = "fill") + aes(PPNET, fill = Q23_r) + facet_wrap(~Q23_q) + ggtitle("By internet availability")